Advanced driver assistance systems (ADAS) are systems developed to automate, adapt, and/or enhance vehicle systems for safety and better driving. Safety features in vehicles are designed to avoid collisions and accidents by offering technologies that alert the driver to potential problems, or to avoid collisions by implementing safeguards and taking over control of the vehicle. Adaptive features may automate lighting, provide adaptive cruise control, automate braking, incorporate GPS/ traffic warnings, connect to smartphones, alert driver to other cars or dangers, keep the driver in the correct lane, or show if vehicles and/or objects are present in blind spots.
While sensors are known to provide relatively accurate sensor readings (sensor data), there are certain driving conditions (e.g., rain, fog, small road debris, etc.) that may affect the accuracy of certain sensors. As ADAS systems become more prevalent in automobiles, it becomes more important to determine and communicate a confidence level on the accuracy and/or integrity of the sensors during operation. In certain instances, ADAS systems may fail to engage if the sensors are unable to obtain the necessary data. In other instances, ADAS systems may continue to operate when sufficient sensor data is received, but the sensor data is not fully accurate and/or contains certain deficiencies in the data. Accordingly, technologies and techniques are needed to establish a confidence (reliability) factor for sensor data. Furthermore, technologies and techniques are needed to graphically display one or more confidence factors for sensors in a manner that is not distracting and/or overwhelming for the driver/user.